Individual interest and learning in secondary school STEM education

Main Article Content

Erkka Laine
Marjaana Veermans
Andreas Gegenfurtner
Koen Veermans, Dr.


Interest research offers different hypotheses about the association between interest and learning outcomes. The standard hypothesis proposes that interest predicts learning outcomes: people acquire new knowledge about a topic they find interesting. The affective by-product hypothesis assumes that learning predicts interest: by learning something, people develop an interest in this topic. Finally, the reciprocal hypothesis states that interest and learning covary. This longitudinal study aimed to test the predictive validity of these three hypotheses in the context of secondary school STEM education. The participants were 104 Finnish 7th grade students aged 12-14. Data were collected at three times during the school year through questionnaires and grade evaluations in mathematics and biology. A partial least squares (PLS) path modeling approach was used to determine the relationships between interest and course grades across the three measurement points: at the beginning of the autumn semester, at the beginning of the spring semester, and after the spring semester at the end of the school year. The results differed between the autumn and spring semesters: During the autumn semester, students’ interest predicted their grades, whereas during the spring semester, grades predicted their interest. These findings indicate that the relationships between students’ individual interest towards science and mathematics with learning vary. As a practical implication, more focus should be put on when and what type of performance feedback is given to students with differing interest profiles.    

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How to Cite
Laine, E., Veermans, M., Gegenfurtner, A., & Veermans, K. (2020). Individual interest and learning in secondary school STEM education. Frontline Learning Research, 8(2), 90 - 108.
Author Biography

Erkka Laine, University of Turku

Department of Teacher Education, Doctoral student


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